class_docstr: Dummy Forecaster for initial pycaret pipeline
code: def _predict(self, fh=None, X=None):
      self.check_is_fitted()
      if fh is not None:
          preds = pd.Series([-99_999] * len(fh))
      elif self._fh_len is not None:
          # fh seen during fit
          preds = pd.Series([-99_999] * self._fh_len)
      else:
          raise ValueError(
              f"{type(self).__name__}: `fh` is unknown. Unable to make predictions."
          )
  
      return preds
  
file_path: pycaret/pycaret/utils/time_series/forecasting/models.py
imports: import pandas
  from sktime.forecasting.base import BaseForecaster
  from pycaret.utils.time_series import TSExogenousPresent
label_desc: Use image node_id 2 for calling the DummyForecaster obj's underlying member method code with example usage: obj._predict(fh, X) and returns: preds